Transfer of height datum across seas using GPS leveling, gravimetric geoid and corrections based on a polynomial surface

Deng, Xiao‐Fang; Hua, Xing; You, Yangsheng

doi:10.1016/j.cageo.2012.07.033

Cited by 14 publications

(5 citation statements)

References 13 publications

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“…The spatial trend field matrix F constructed by f(si) is an ill-conditioned matrix in high-speed railways, which causes the solution of βt to be unstable and volatile using the least square method 23 . For this reason, this paper uses the adaptive spectrum correction method to calculate βt 19 .…”

Section: Methodsmentioning

confidence: 99%

Settlement monitoring data fusion approach for high-speed railways based on GNSS and InSAR

Qiu,

Wang,

Zhang

et al. 2023

J. Appl. Rem. Sens.

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.The high-precision and high spatio-temporal resolution settlement time series data generated by integrating Global Navigation Satellite System (GNSS) and Interferometric Synthetic-Aperture Radar (InSAR) data are of great value for the safe operation of high-speed railways. The GNSS monitoring stations and InSAR monitoring area present zonal distribution along the high-speed railways, which causes the spatial matrix of the GNSS and InSAR data fusion model to be an ill-conditioned matrix. The inverse of the ill-conditioned space matrix is unstable, and it is difficult to estimate the optimal parameter value of the fusion model, which leads to low accuracy and large fluctuations in the fusion of GNSS and InSAR data. We propose a spatio-temporal filter fusion (STFF) method to solve the influence of the ill-conditioned space matrix on the fusion of GNSS and InSAR data, which realizes the high-precision fusion of GNSS and InSAR data along the high-speed railway. First, we propose the kriging model of the adaptive spectral correction method to construct the spatial model of GNSS and InSAR data, avoiding the generation of the ill-conditioned space matrix. Second, iterative almost unbiased estimation is used to obtain the weights of GNSS and InSAR data, avoiding the occurrence of negative variance components. The experimental data are fused using STFF, the spatio-temporal Kalman filter (STKF) method, and the spatio-temporal random effect (STRE) fusion method, respectively. The research results show that the comprehensive performance of STFF is significantly better than that of STKF and STRE. In the spatial domain, the root mean square error (RMSE) reduced by 47% and 46% compared with STKF and STRE, respectively, and the structural similarity index increased by 22% and 16% compared with STKF and STRE, respectively. In the time domain, the RMSE reduced by 29% and 34% compared with STKF and STRE, respectively.

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Section: Methodsmentioning

confidence: 99%

Settlement monitoring data fusion approach for high-speed railways based on GNSS and InSAR

Qiu,

Wang,

Zhang

et al. 2023

J. Appl. Rem. Sens.

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“…With the help of these points, local geoid model is formulated [15,16]. Taking the size of the study area and the number of reference points into consideration, Eqs.…”

Section: Polynomial Interpolationmentioning

confidence: 99%

“…In order to generate the geoid model at reference stations, geoid heights are calculated by Eq. (3) [6,16,18].…”

Section: Polynomial Interpolationmentioning

confidence: 99%

Local geoid determination in strip area projects by using polynomials, least-squares collocation and radial basis functions

Doğanalp

Selvi

2015

Measurement

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“…While forming local GPS/leveling geoid model, in the study area one makes use of the reference stations whose ellipsoidal (h) and Helmert orthometric (H) heights are known. Using a data set which consists of good positional estimates within a few cm, one can form a local geoid model by using an analytic interpolation polynomial (Sahrum et al, 2009;Deng et al, 2013). Polynomial interpolation methods are widely used especially in determining local geoid heights with the GPS/leveling method.…”

Section: Interpolation By Polynomial Curve Fittingmentioning

confidence: 99%

“…namely geoid. Three types of leveling, i) geometric, ii) trigonometric and iii) GPS are used for the differential measurements to produce the heights with respect to the plumb line and geoid model (Deng et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Geoid height computation in strip-area project by using least-squares collocation

Doğanalp¹

2015

Acta Geodynamica Et Geomaterialia

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GPS/leveling technique is the most effective engineering method for the determination of heights and height differences. This method is based on the principal of conversion of ellipsoid heights to orthometric heights. For transformation, polynomial surface models are generally used for study region or area. The accuracy of results depends on the location and distribution of selected reference stations with known ellipsoidal and orthometric heights. Especially, in the strip area projects (highway, railway, channel etc.) polynomial curve model is used instead of polynomial surface model due to reference stations disturbing along a route. In this research, Least Squares Collocation (LSC) methods used in determining the geoid heights of a strip area were examined. For this purpose, GPS/leveling data of Bozkurt-Dinar (Afyonkarahisar) train project which is approximately 75 km was used in order to examine LSC methods. The ground control stations of the project were classified as reference and test for the purpose of this research. The geoid heights of test stations were calculated by curve polynomial with different degrees. Additionally geoid heights at the same points were calculated using polynomial curve fitting based on LSC which is suggested by this research. The geoid heights by computed using LSC approach when compared to polynomial curve method were observed to yield better results. ARTICLE INFO

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Transfer of height datum across seas using GPS leveling, gravimetric geoid and corrections based on a polynomial surface

Cited by 14 publications

References 13 publications

Settlement monitoring data fusion approach for high-speed railways based on GNSS and InSAR

Settlement monitoring data fusion approach for high-speed railways based on GNSS and InSAR

Local geoid determination in strip area projects by using polynomials, least-squares collocation and radial basis functions

Geoid height computation in strip-area project by using least-squares collocation

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